Artificial intelligence based analysis for magnetized casson fluid in partially heated cavity rooted with heated fin

Abstract

The examination of heat transfer aspects in Casson fluid equipped in cavities is considered important for improved coating, molding, extrusion, designing systems with high efficiency, enhancing medical applications, and understanding industrial and natural processes. Therefore, exploring the heat transfer in Casson remains of great interest to researchers. Owning to such interest we offer artificial neural networks study of heat transfer aspects in partially heated hexagonal cavity in the presence of natural convection and magnetic field. The cavity is rooted with a uniformly heated Y-shaped fin. The lower wall is hot while the top wall is considered an adiabatic. Left and right walls are taken cold. The flow equations are solved by finite element method (FEM). The artificial neural network (ANN) model is trained by using the Levenberg-Marquard algorithm and the Nusselt number is estimated along the uniformly heated fin for both cases namely (i) heated tip and (ii) cold tip. This configuration demonstrates how convective currents and temperature distributions get more intricate and noticeable as the Rayleigh number increases. We noticed that uniformly heated fins effectively regulate and enhance convection, which is important for heat management applications.